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Int J Cardiol. 2014 Dec 20;177(3):1031-5. doi: 10.1016/j.ijcard.2014.09.124. Epub 2014 Oct 2.

Developing a risk prediction model for survival to discharge in cardiac arrest patients who undergo extracorporeal membrane oxygenation.

Author information

1
Department of Critical Care Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea; Department of Medicine, Korean Armed Forces Capital Hospital, Seongnam, South Korea.
2
Department of Critical Care Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea; Division of Cardiology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, South Korea. Electronic address: jhysmc@gmail.com.
3
Division of Cardiology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, South Korea.
4
Department of Thoracic and Cardiovascular Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
5
Department of Critical Care Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
6
Department of Critical Care Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea; Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.

Abstract

BACKGROUND:

Limited data are available on a risk model for survival to discharge after extracorporeal membrane oxygenation (ECMO)-assisted cardiopulmonary resuscitation (ECPR). We aimed to develop a risk prediction model for survival to discharge in cardiac arrest patients who undergo ECMO.

METHODS:

Between January 2004 and December 2012, 505 patients supported by ECMO were enrolled in a retrospective, observational registry. Among those, we studied 152 adult patients with in-hospital cardiac arrest. The primary outcome was survival to discharge. A new predictive scoring system, named the ECPR score, was developed to monitor survival to discharge using the β coefficients of prognostic factors from the logistic model, which were internally validated.

RESULTS:

In-hospital death occurred in 104 patients (68.4%). In multivariate logistic regression, age ≤ 66, shockable arrest rhythm, CPR to ECMO pump-on time ≤ 38 min, post-ECMO arterial pulse pressure > 24 mmHg, and post-ECMO Sequential Organ Failure Assessment score ≤ 14 were independent predictors for survival to discharge. Survival to discharge was predicted by the ECPR score with a c-statistics of 0.8595 (95% confidence interval [CI], 0.80-0.92; p<0.001) which was similar to the c-statistics obtained from internal validation (training vs. test set; c-statistics, 0.86 vs. 0.86005; 95% CI, 0.80-0.92 vs. 0.77-0.94). The sensitivity and specificity for prediction of survival to discharge were 89.6% and 75.0%, respectively, when the ECPR score was >10.

CONCLUSIONS:

The new risk prediction model might be helpful for decisions about ECPR management and could provide better information regarding early prognosis.

KEYWORDS:

Cardiopulmonary resuscitation; Extracorporeal membrane oxygenation; Predictor

PMID:
25443259
DOI:
10.1016/j.ijcard.2014.09.124
[Indexed for MEDLINE]

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